Clustering search results. Part III: the synergy of metasearching and clustering
| Published date | 26 June 2007 |
| DOI | https://doi.org/10.1108/14684520710764131 |
| Date | 26 June 2007 |
| Pages | 376-382 |
| Author | Peter Jacsó |
| Subject Matter | Information & knowledge management,Library & information science |
SAVVY SEARCHING
Clustering search results. Part III:
the synergy of metasearching
and clustering
Pe
´ter Jacso
´
University of Hawaii, Hawaii, USA
Abstract
Purpose – The purpose of this paper is to further examine clustering search results.
Design/methodology/approach – The paper describes and illustrates the most powerful synergy
created by the intelligent combination of metasearching and clustering on the fly through Central
Search and PolyMeta.
Findings – The study finds that the combination of metasearching and clustering, although two
opposite functions, can produce effective synergy.
Originality/value – This paper looks at the intelligent combination of metasearching and clustering
in the form of Central Search and PolyMeta, giving a new step in savvy searching.
Keywords Search engines,Cluster analysis, Worldwide web
Paper type General review
The previous two parts of this column looked at some of the clustering options of results
offered by generic web wide search engines like Ask.com (using Vivisimo), Gigablast,
WiseNut and Exalead, retrieved from hundreds of millions of unstructured, openaccess
web pages. The second part explained and showed the use of clustering of results
retrieved from highly structured, distinct databases of much smaller size (typically less
than a million records), and yielding far fewer records in the range of a few hundred to a
few thousands hits for two to three-word queries. This section describes and illustrates
the most powerful synergy created by the intelligent combination of metasearching and
clustering on the fly through Central Search and PolyMeta. The most powerful and
popular federated search engines, such as Muse, MetaLib, WebFeat and TDNet, are
working on this type of combination and are likely to release operational versions later
this year. Using such systems will certainly represent a savvy search strategy.
Conflicting moves?
At first, the combination of metasearching and clustering may look more like an
interference than a synergy. After all, we are using metasearching (or federated
searching) to submit a query to several databases in order to enhance resource
discovery by learning about several distinct resources which may provide more and
better answers to our information need. In other words we are broadening the search.
After that step we do just the opposite by clustering the results to reduce the result set,
and to retrieve the most relevant and pertinent (subjectively relevant) items. If well
done, this combination can produce effective synergy. This is possible because
software can retrieve millions of records even from disparate databases in seconds,
then sift through all of them to extract and cluster them by a variety of criteria.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1468-4527.htm
OIR
31,3
376
Online Information Review
Vol. 31 No. 3, 2007
pp. 376-382
qEmerald Group Publishing Limited
1468-4527
DOI 10.1108/14684520710764131
To continue reading
Request your trial